Memory as Infrastructure: Reliability Engineering for Persistent Agent Memory in Months-Long LLM-Assisted Development
On the map: LLM agents and tool use → Agent memory systems
Abstract (arXiv)
LLM coding agents are crossing from task-scale to project-scale: single assisted efforts that run for months, across repeated context compactions, on codebases far larger than any context window. We report operational experience from one such effort (a research project under a single continuous Claude Code session line since January 2026, driving a 633,000-line codebase, with its memory subsystem continuously instrumented since July 2026) and describe SIx Harness, the open-source memory and continuity infrastructure that emerged from keeping it coherent. The harness combines per-project long-term memory (hybrid lexical-vector retrieval over SQLite, fully local), precision-gated context injection, anti-recurrence stores for decisions and dead-ends, conventions engineered to survive compaction, and, the part we argue is missing from operational practice, reliability engineering for the memory subsystem itself: a session-start health gate with discriminated failure modes, heartbeat telemetry designed so that no enumerated failure mode can pass unrecorded, and alert-fatigue budgeting borrowed from SRE practice. We present what we believe is the first months-scale instrumented operational record of a persistent agent-memory subsystem in production development use: 78,933 hook invocations; 85 recorded failures, none silent: 84 in the subsystem's first three weeks, one since, none in the final 20 days; an injection layer whose ten-day precision instrument shows zero false fires against an intact denominator; and three production incidents traced from instrument reading to structural fix. From the record we distill seven design principles, state our limitations plainly (N=1, no control arm, self-reported), and publish a tagged pre-registered ablation protocol that any team can run with the released MIT-licensed kit.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Agent memory systems, one of 16 directions in LLM agents and tool use. Builds on 23 of its 53 references that are in the map. First posted on arXiv 31 Aug 2026.
Builds on
23 of 53 references.
Closest ancestors · 6
Same direction, newest first
- 2026A-TMA: Decoupling State-Aware Memory Failures in Long-Term Agent Memory2 Jul
- 2026STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?7 May
- 2025Memory in the Age of AI Agents15 Dec
- 2025Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory28 Apr
- 2025A-MEM: Agentic Memory for LLM Agents17 Feb
- 2025Zep: A Temporal Knowledge Graph Architecture for Agent Memory20 Jan
Other references · 17
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- 2023MemGPT: Towards LLMs as Operating Systemscited by 1,389
- 2023Large Language Models Can Be Easily Distracted by Irrelevant Contextcited by 841
- 2023Cognitive Architectures for Language Agentscited by 429
- 2024AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Basescited by 429
- 2023The Impact of AI on Developer Productivity: Evidence from GitHub Copilotcited by 274
- 2025Measuring AI Ability to Complete Long Software Taskscited by 156
- 2025MemOS: A Memory OS for AI Systemcited by 138
- 2025Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivitycited by 101
5 more
- 2026Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systemscited by 9
- 2026Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agentscited by 8
- 2025WhatsCode: Large-Scale GenAI Deployment for Developer Efficiency at WhatsAppcited by 2
- 2026Written by AI, Managed by AI: Semantic Space Control and Index Sickness Elimination Across 391 Consecutive Sessionscited by 1
- 2026Metadata Reconstruction from Values Alone: Recovering Column Semantics in Undocumented Warehousescited by 1
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Not cited yet.
Similar, not cited
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